“Summer used to be about putting away the heating bills. Now it’s about calculating if your GPU setup will turn your home office into a sauna.”
— Wing

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🌡️ The Heat Season Arrives

June 2025, and once again I’m staring at my rig while the temperature climbs outside.

Two years ago, this conversation was academic. Now? My RTX 4090 is generating enough BTUs to heat a small apartment, my power bank collection could run a small electronics store, and I’m genuinely considering whether the latest-and-greatest is worth the environmental reality it creates.

“Back in my day, we overclocked our Pentiums to run Quake faster. Now we’re doing it for language models.”
— Wing, mid-rant, 2022

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In the year 2022, a new frontier opened up for hobbyists and developers alike: Large Language Models (LLMs) stopped being pure research tools and started becoming part of the daily build cycle for curious engineers and indie coders. But with that shift came a new dilemma—do you run your AI workloads locally, or pipe them out to the cloud?